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In 1954, IBM demonstrated the ability to translate Russian sentences into English using machine translation on an IBM 701 mainframe. While simple by today's standards, the demonstration identified the massive advantages of language translation. In this article, we'll examine natural language processing (NLP) and how it can help us to converse more naturally with computers. NLP is one of the most important subfields of machine learning for a variety of reasons. Natural language is the most natural interface between a user and a machine. In the ideal case, this involves speech recognition and voice generation. Even Alan Turing recognized this…
Apr 09, 2019
Artificial intelligenceDeep learning+
Code Pattern
Create a real-time object detection app using Watson Machine Learning
Build an iOS game powered by Core ML and Watson Visual Recognition
Deploy a deep learning-powered ‘Magic cropping tool’
Article
IBM’s approach to open technology
Workshop
Apr24
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Featured | Code Pattern
Apr 22, 2019
Artificial intelligenceCloud+
Create your own music based on your arm movements in front of a webcam.
Apr 11, 2019
Apache SparkArtificial intelligence+
Train a machine learning model to predict type 2 diabetes using synthesized patient health records.
Tutorial
AndroidArtificial intelligence+
Build a fun treasure hunt game that uses visual recognition.
Apr 16, 2019
Artificial intelligenceVision
Use drone aerial images, Watson Studio, and Watson Visual Recognition to survey wildfire-damaged neighborhoods and identify burned homes and intact homes.
Blog
Apr 12, 2019
Artificial intelligenceConversation+
Learn how to incorporate AI into your apps to help mitigate the risks from natural disasters.
Learn how you can use machine learning to train your own custom model without substantive computing power and time.
Follow your favorite players without missing any of the best moments.
Other
Artificial intelligenceIoT+
This video tutorial demonstrates a Node-RED flow that uses Watson Speech-to-Text APIs to transcribe the words that are being spoken, that counts how many words are being said in a given time, and then passes a message along to an IoT connected device (the GlowOrb) with MQTT telling it to…
AnalyticsArtificial intelligence+
IBM Cognos Analytics 11.1 is a the state-of-the-art, self-service analytics platform. It introduces many AI-infused features to help you quickly discover hidden insights, recommend visualizations, and make conversation in natural language.
Series
Apr 08, 2019
Artificial intelligenceData science+
Get an overview of the Snap ML library, which provides high-speed training of popular machine learning models, and look at several use cases for using it.
A process model and an architectural decisions guide to map individual technology components to the reference architecture and guidelines for deployment considerations.
Apr 03, 2019
Explore this end-to-end, deep learning platform for data scientists.
Apr 02, 2019
In this tutorial you will learn how to create a Node-RED Starter application that can be used to connect Watson AI services Speech to Text, Language Translator, and Text to Speech to create a spoken universal translator.
Apr 01, 2019
Take a look at the testing of generalized linear models (GLMs) from the Snap ML library on three different use cases that are related to the financial services sector.
Deployable
Mar 29, 2019
Upscale an image by a factor of 4, while generating photo-realistic details.
Detect the sentiment captured in short pieces of text
Mar 28, 2019
Use an open source object detector deep learning model to display and filter objects recognized in an image in a web application.
Artificial intelligenceCaffe2+
Deploy and consume a deep learning platform on Kubernetes, offering TensorFlow, Caffe, PyTorch etc. as a service.
AnalyticsApache Spark+
Use Watson Studio and scalable machine-learning tool R4ML to load dataset and do uniform sampling for visual data exploration.
Identify nuclei in a microscopy image and assign each pixel of the image to a particular nucleus
Video
Artificial intelligenceMAX - Model Asset eXchange
Use a free, open-source deep learning model to detect different types of objects in an image, then interact with them in a drag-and-drop web application.
Leverage Tensorflow and Fabric for Deep Learning to train and deploy Fashion MNIST model on Kubernetes.
Create bar charts, line charts, scatter plots, pie charts, histograms, and maps without any coding.
Leverage R4ML and Watson Studio to conduct preprocessing and exploratory analysis with big data.
Artificial intelligenceDocker+
Use an open source age estimation deep learning model to detect faces and estimate their age in a web application.
Process image, video, audio, or text data using deep learning models from the Model Asset Exchange in Node-RED flows.
Learn about a new batch of models, encompassing audio, natural language processing, and image recognition.
Use an open source image segmentation deep learning model to detect different types of objects from within submitted images, then interact with them in a drag-and-drop web application interface to combine them or create new images.
Artificial intelligenceJupyter Notebook+
Utilize the power of Node.js in Jupyter Notebooks with pixiedust_node, an open source Python library.
Train a deep learning language model in a notebook using Keras and Tensorflow.
Use Jupyter Notebooks with IBM Watson Studio to build an interactive recommendation engine PixieApp.
This developer pattern demonstrates the key elements of creating a recommender system by using Apache Spark and Elasticsearch.
Use an open source image caption generator deep learning model to filter images based on their content in a web application.
Mar 27, 2019
Artificial intelligenceAudio Modeling+
Converts spoken words into text form.
Mar 26, 2019
Learn how to launch a chatbot on the TJBot, which has a Raspberry Pi that is equipped with the USB microphone and a small portable speaker. You use with Watson Speech to Text and Watson Text to Speech services that generate speech for users and convert sounds into text for…
Mar 25, 2019
Artificial intelligence
Learn how to combine cloud technologies to create a diverse, interconnected system of services
Artificial intelligenceConversation
Create your own personal assistant with Q.bo One
Mar 21, 2019
Artificial intelligenceMachine learning+
Use Watson Natural Language Understanding to automatically store the bookmarked URL in proper directory structure.
Mar 19, 2019
Learn how IBM has played, and continues to play, a leading role in the evolution of open source and how we leverage that leadership to deliver world-class offerings and solutions that benefit our customers.
Before open source was cool, IBM worked to establish open source as technology that's safe (and good!) for the enterprise.
Mar 18, 2019
The Model Asset Exchange is place for developers to find and use free and open source deep learning models. Complete this learning path to explore the model zoo and learn how to consume these models in a web application or Node-RED flow.
Mar 15, 2019
Create a data mart for Watson Machine Learning deployments and include steps for performance, bias, and quality monitor configurations.
Detect faces in an image and predict the emotional state of each person
Mar 14, 2019
AnalyticsArtificial intelligence
On March 15, we're featuring the women from the IBM Developer Advocates team. Tune in live to hear what they're up to. Come ready to learn and ask questions in the chat.
Mar 13, 2019
Artificial intelligenceCloud Foundry+
Step through the process of getting data and training a model to deploy as a web service to Cloud Foundry.
Mar 12, 2019
Create a custom Watson Speech to Text model for handling specialized domain data, and use domain-specific data to improve the acuracy of the service.
Dojo
Mar 07, 2019
See what you can do with Watson technology and open source hardware
Artificial intelligenceWatson Studio
This video series serves as a tutorial for learning how to use IBM Watson Studio.
Mar 06, 2019
Addressing the challenges of managing AI models at scale
Artificial intelligenceCloud
Learn how you can join this year's coding challenge.
Mar 05, 2019
How to extract the most information out of each interface type.
Going beyond invoking APIs to building AI-driven applications
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